In this thesis, several algorithms for distributed model predictive control over digital communication networks with parallel computation are developed and analyzed. Distributed control aims at efficiently controlling large scale dynamical systems which consist of interconnected dynamical systems by means of communicating local controllers. Such distributed control problems arise in applications such as chemical processes, formation control, and control of power grids. In distributed model predictive control the underlying idea is to solve a large scale model predictive control problem in a distributed fashion in order to achieve faster computation and better robustness against local failures. Distributed model predictive control often heavily relies on frequent communication between the local model predictive controllers. However, a digital communication network may induce uncertainties such as a communication delays, especially if the load on the communication network is high. One topic of this thesis is to develop a distributed model predictive control algorithm for subsystems interconnected by constraints and common control goals which is robust with respect to time-varying communication delays.

This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.

Event-based systems are a class of reactive systems deployed in a wide spectrum of engineering disciplines including control, communication, signal processing, and electronic instrumentation. Activities in event-based systems are triggered in response to events usually representing a significant change of the state of controlled or monitored physical variables. Event-based systems adopt a model of calls for resources only if it is necessary, and therefore, they are characterized by efficient utilization of communication bandwidth, computation capability, and energy budget. Currently, the economical use of constrained technical resources is a critical issue in various application domains because many systems become increasingly networked, wireless, and spatially distributed. Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers: Methods of analysis and design of event-based control and signal processing Event-driven control and optimization of hybrid systems Decentralized event-triggered control Periodic event-triggered control Model-based event-triggered control and event-triggered generalized predictive control Event-based intermittent control in man and machine Event-based PID controllers Event-based state estimation Self-triggered and team-triggered control Event-triggered and time-triggered real-time architectures for embedded systems Event-based continuous-time signal acquisition and DSP Statistical event-based signal processing in distributed detection and estimation Asynchronous spike event coding technique with address event representation Event-based processing of non-stationary signals Event-based digital (FIR and IIR) filters Event-based local bandwidth estimation and signal reconstruction Event-Based Control and Signal Processing is the first extensive study on both event-based control and event-based signal processing, presenting scientific contributions at the cutting edge of modern science and engineering.

Networked Control Systems: Cloud Control and Secure Control explores new technological developments in networked control systems (NCS), including new techniques, such as event-triggered, secure and cloud control. It provides the fundamentals and underlying issues of networked control systems under normal operating environments and under cyberphysical attack. The book includes a critical examination of the principles of cloud computing, cloud control systems design, the available techniques of secure control design to NCS's under cyberphysical attack, along with strategies for resilient and secure control of cyberphysical systems. Smart grid infrastructures are also discussed, providing diagnosis methods to analyze and counteract impacts. Finally, a series of practical case studies are provided to cover a range of NCS's. This book is an essential resource for professionals and graduate students working in the fields of networked control systems, signal processing and distributed estimation. - Provides coverage of cloud-based approaches to control systems and secure control methodologies to protect cyberphysical systems against various types of malicious attacks - Provides an overview of control research literature and explores future developments and solutions - Includes case studies that offer solutions for issues with modeling, quantization, packet dropout, time delay and communication constraints

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.

This book investigates distributed cooperative control and communication of MASs including linear systems, nonlinear systems and multiple rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The approaches of this book consist of model-based and data-driven control such as predictive control, event-triggered control, optimal control, adaptive dynamic programming, etc. From this book, readers can learn about distributed cooperative control methods, data-driven control, finite-time stability analysis, cooperative attitude control of multiple rigid bodies. Some fundamental knowledge prepared to read this book is finite-time stability theory, event-triggered sampling mechanism, adaptive dynamic programming and optimal control.

This book aims to explain how collective behavior is formed via local interactions under imperfect communication in complex networked systems. It also presents some new distributed protocols or algorithms for complex networked systems to comply with bandwidth limitation and tolerate communication delays. This book will be of particular interest to the readers due to the benefits: 1) it studies the effect of time delay and quantization on the collective behavior by non-smooth analytical technique and algebraic graph theory; 2) it introduces the event-based consensus method under delayed information transmission; In the meantime, it presents some novel approaches to handle the communication constraints in networked systems; 3) it gives some synchronization and control strategies for complex networked systems with limited communication abilities. Furthermore, it provides a consensus recovery approach for multi-agent systems with node failure. Also, it presents interesting results about bipartite consensus and fixed-time/finite-time bipartite consensus of networks with cooperative and antagonistic interactions.

This book constitutes the refereed proceedings of the 20th International Conference on Distributed and Computer and Communication Networks, DCCN 2017, held in Moscow, Russia, in September 2017. The 39 full papers and the two short papers were carefully reviewed and selected from 176 submissions. The papers cover the following topics: computer and communication networks architecture optimization; control in computer and communication networks; performance and QoS/QoE evaluation in wireless networks; analytical modeling and simulation of next-generation communications systems; queueing theory and reliability theory applications in computer networks; wireless 4G/5G networks, cm- and mm-wave radio technologies; RFID technology and its application in intellectual transportation networks; Internet of Things, wearables, and applications of distributed information systems; probabilistic and statistical models in information systems; mathematical modeling of high-tech systems; mathematical modeling and control problems; distributed and cloud computing systems, big data analytics.

Process Systems Engineering brings together the international community of researchers and engineers interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 13th International Symposium on Process Systems Engineering PSE 2018 event held San Diego, CA, July 1-5 2018. The book contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE. - Highlights how the Process Systems Engineering community contributes to the sustainability of modern society - Establishes the core products of Process Systems Engineering - Defines the future challenges of Process Systems Engineering